Does an imaginary trip to the future increase people's contribution to climate change mitigation?

Last registered on March 13, 2023
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Pre-Trial

Trial Information

General Information

Title
Does an imaginary trip to the future increase people's contribution to climate change mitigation?
RCT ID
AEARCTR-0010614
Initial registration date
December 12, 2022

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
January 03, 2023, 11:51 AM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
March 13, 2023, 11:02 PM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country
China
Region
Xi'an

Primary Investigator

Name
Botao Qin
Affiliation
Xi'an Jiaotong University
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Other Primary Investigator(s)

PI Name
Nan Zhang
PI Affiliation
Xi'an Jiaotong University
Contact Investigator
PI Name
Yaru Wang
PI Affiliation
Xi'an Jiaotong University
Contact Investigator

Additional Trial Information

Status
In development
Start date
2022-12-16
End date
2023-12-17
Keywords
Behavior, Environment & Energy, Lab
Additional Keywords
imaginary-trip-to-the-future, climate change mitigation, discount rate
JEL code(s)
C91, C92, D64, Q56
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Intergenerational equity is a problem in our world. We consume too many resources today and the current way of living is not sustainable. How to help people avoid short-sightedness and increase their concern for the future? Some scholars use future design to find mechanisms to make people care about long-run problems. We study how the imaginary trip to the future as a mechanism will affect people's attitudes toward future generations. Using an imaginary trip to the future, we measure if it affects people's discount rate and also people's contribution to climate change mitigation.
External Link(s)

Registration Citation

Citation
Qin, Botao, Yaru Wang and Nan Zhang. 2023. "Does an imaginary trip to the future increase people's contribution to climate change mitigation?." AEA RCT Registry. March 13. https://doi.org/10.1257/rct.10614-1.3
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
We plan to use the forward-and-backward (FAB) mechanism as an intervention to see if it can increase people's futurability and their donation to the climate fund. The futurability will be measured by the discount rate. In addition, we will also use a hypothetical intervention for the elicitation of the discount rate.
Intervention Start Date
2023-02-20
Intervention End Date
2023-12-17

Primary Outcomes

Primary Outcomes (end points)
discount rate; contributions to the climate fund
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
climate attitudes
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will recruit students from the university to run a two-by-two lab experiment.
Experimental Design Details
Randomization Method
randomization done in office by a computer
Randomization Unit
experimental sessions
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
200 students
Sample size: planned number of observations
200 students
Sample size (or number of clusters) by treatment arms
50 students control, 50 students forward-and-backward, 50 students hypothetical discount rate task, 50 students both treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Using the power calculation from Gerber and Green (2012), beta=normdist{effect size*sqrt(N)/(2*sigma) - normsinv(1-alpha/2)}, we want to achieve a power of 0.8, that is, beta=0.8, N=100, the level of significance alpha=0.05. From the literature, we find the standard deviation of the discount rate elicited is around 1.255. Using the above formula, we can calculate the effect size equals 0.703, which is 56% of the standard deviation.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials